Imaging compensation of orbital motion for geostationary meteorological satellite

Wang LYU; Yaohai DONG; Yili SHEN; Zhiqing ZHANG; Wenqiang CHEN

doi:10.11834/jrs.20198061

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Imaging compensation of orbital motion for geostationary meteorological satellite
Vol. 23, Issue 2, Pages: 185-195(2019)
Received：06 February 2018，

Accepted：07 May 2018，

Published：2019-03
DOI： 10.11834/jrs.20198061
稿件说明：

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吕旺, 董瑶海, 沈毅力, 张志清, 陈文强. 2019. 静止气象卫星轨道运动的成像补偿研究. 遥感学报, 23(2): 185–195 DOI： 10.11834/jrs.20198061.

Lyu W, Dong Y H, Shen Y L, Zhang Z Q and Chen W Q. 2019. Imaging compensation of orbital motion for geostationary meteorological satellite. Journal of Remote Sensing, 23(2): 185–195 DOI： 10.11834/jrs.20198061.

摘要

为进一步提高观测频次和信噪比，近年来各国新一代静止气象卫星均采用三轴稳定工作模式对地扫描成像。为了精确提取遥感目标物所在地点关于地表、云和大气状态的定量参数产品，必须要解决图像配准和定位问题。轨道漂移运动引起卫星视轴在地球表面上移动，导致连续图像之间产生相对位移，影响云图动画的图像配准精度。以2016年12月发射的中国风云四号卫星成像仪为研究对象，给出了图像参考基准的严密定义，研究了一种轨道运动补偿OMC(Orbit Motion Compensation)方法。通过给成像仪2维扫描机构增加转角补偿的方法在卫星上实时引导视线扫描路径，卫星相当于在理想轨道位置的视角成像。得到的遥感图像均被配准到地球固定网格FG(Fixed Grid)，保持相对固定的几何定位关系。由于这种在卫星上完成的补偿剥离了L0级图像数据与卫星轨道测量信息之间的关系，从根源上保证了原始图像的长周期定位稳定性。为证明方法的正确性，利用风云四号卫星在轨测试的遥感图像L0级数据进行了试验验证。结果表明，云图动画中南北方向相对运动距离由973.0 μrad缩小至75.6 μrad，东西方向由205.8 μrad缩小至81.2 μrad。星上轨道运动补偿有效削弱了周期性轨道运动对图像定位与配准的干扰，显著提升图像配准精度。针对未来带有长线阵的新型静止卫星成像仪发展趋势，分析了进行星上轨道运动补偿时引起的长线阵探测器边缘像元误差问题，提出了采用电推进系统对卫星轨道倾角进行高精度保持控制来降低边缘误差的解决方案。

Abstract

In recent years

a new generation of stationary meteorological satellites in various countries has adopted the three-axis stabilized mode of operation to scan the Earth for further improvement of observation frequency and signal–noise ratio. Image registration and navigation problems must be solved to accurately extract quantitative parameters of the Earth’s surface

clouds

and atmosphere at remote sensing target locations. Orbital drift movement is one of the main causes of satellite line-of-sight movement on the Earth’s surface. The relative movement generated between consecutive images affects the image registration accuracy of cloud animation. In this study

the imager on the Chinese FY-4 satellite that was launched in December 2016 is used as the research object. Moreover

a strict definition of image reference is given

and an orbital motion compensation method (OMC) is studied. By adding scan compensation to the imager 2-D scanning mechanism

the scanning path of the line of sight is navigated on the satellite in real time. Satellites are equivalent to viewing at ideal orbital positions. As a result

satellite remote sensing images are accurately registered to the Earth-fixed grid

and a relatively fixed geometric relationship is maintained. The correlation between L0 data and the measurement information of satellite orbit is removed due to the compensation performed on the satellite. Therefore

the long-term registration stability of the original image is guaranteed from the root. L0 remote sensing data from the FY-4 on-orbit test are used for experimental verification to prove the accuracy of the method. The results show that the relative movement of the north–south directions of the cloud animation is reduced from 973.0 μrad to 75.6 μrad (3σ) and that of the east–west direction is reduced from 205.8 μrad to 81.2 μrad (3σ). The interference of the orbital motion on the image navigation and registration is effectively reduced by the OMC on the satellite. In view of the development trend of the future imager of the geostationary meteorological satellite

the problem of the edge pixel error of the long aperture array detector caused by satellite orbital motion compensation is analyzed. Furthermore

a solution to reduce the edge error by maintaining the satellite near 0° inclination using an electric propulsion system is proposed.

关键词

Keywords

references

Bay H, Ess A, Tuytelaars T and Van Gool L. 2008. Speeded-up robust features (SURF). Computer Vision and Image Understanding, 110(3): 346–359

Carlomusto M. 2017. Product definition and users’ guide (PUG) volume 5: level 2+ products for geostationary operational environmental satellite R series (GOES-R) core ground segment. CDRL SE-16. Melbourne, Florida: Harris Corporation Government Communications Systems

Carr J L. 2009. Twenty-five years of INR. The Journal of the Astro- nautical Sciences, 57(1/2): 505–515

董瑶海. 2016. 风云四号气象卫星及其应用展望. 上海航天, 33(2): 1–8

Dong Y H. 2016. FY-4 meteorological satellite and its application prospect. Aerospace Shanghai, 33(2): 1–8 (

EUMETSAT. 2013. Coordination Group for Meteorological Satellites LRIT/HRIT Global Specification. CGMS/DOC/12/0017. Darmstadt: CGMS

Griffith P C. 2006. ABI delivers significantly increased capabilities over current imagers//Proceedings of the 4th GOES Users’ Conference. Broomfield, Colorado: [s.n.]

Hogan D, Werbos A, Bentley J, Kennelly E, Puhl-Quinn P, Tully G, Steinfelt E, Zaccheo T S and Davis W. 2014. Multi-mission remote sensing ground processing algorithms//Proceedings of the 94th AMS Annual Meeting. Atlanta, GA: [s.n.]

Kamel A A, Graul D W, Chan F N T and Gamble D W. 1987. Spacecraft camera image registration. U.S., No. 4, 688, 091

Kamel A A, Kim H, Yang D, Park C and Woo J. 2018. Generalized image navigation and registration method based on Kalman filter//Advances in Aerospace Guidance, Navigation and Control. Cham: Springer: 609–630 [DOI: 10.1007/978-3-319-65283-2_33 http://dx.doi.org/10.1007/978-3-319-65283-2_33 ]

Krimchansky A. 2014. GOES-R Series Concept of Operations (CONOPS). 410-R-CONOPS-0008. NOAA

陆风, 张晓虎, 陈博洋, 刘辉, 吴荣华, 韩琦, 冯小虎, 李云, 张志清. 2017. 风云四号气象卫星成像特性及其应用前景. 海洋气象学报, 37(2): 1–12

Lu F, Zhang X H, Chen B Y, Liu H, Wu R H, Han Q, Feng X H, Li Y and Zhang Z Q. 2017. FY-4 geostationary meteorological satellite imaging characteristics and its application prospects. Journal of Marine Meteorology, 37(2): 1–12 (

Lu F, Zhang X H and Xu J M. 2008. Image navigation for the FY2 geosynchronous meteorological satellite. Journal of Atmospheric and Oceanic Technology, 25(7): 1149–1165

卢乃锰, 谷松岩. 2016. 气象卫星发展回顾与展望. 遥感学报, 20(5): 832–841

Lu N M and Gu S Y. 2016. Review and prospect on the development of meteorological satellites. Journal of Remote Sensing, 20(5): 832–841 (

Lyu W, Dai S L, Dong Y H, Shen Y L, Song X Z and Wang T S. 2017a. Attitude motion compensation for imager on Fengyun-4 geostationary meteorological satellite. Acta Astronautica, 138: 290–294

Lyu W, Wang T S, Dong Y H and Shen Y L. 2017b. Imaging navigation and registration for geostationary imager. IEEE Geoscience and Remote Sensing Letters, 14(12): 2175–2179

Schmit T J, Griffith P, Gunshor M M, Daniels J M, Goodman S J and Lebair W J. 2017. A closer look at the ABI on the GOES-R series. Bulletin of the American Meteorological Society, 98(4): 681–698

Shang J, Liu C B, Yang L, Zhang Z Q and Wang J. 2017. Misalignment angle calculation accuracy analysis of three-axis stabilized geostationary satellite. Journal of Geoscience and Environment Protection, 5(12): 153–165

沈毅力, 吕旺, 于永江, 程卫强. 2014. 用于图像定位与配准的扫描辐射计扫描镜热变形模型研究. 上海航天, 31(2): 26–29, 72

Shen Y L, Lv W, Yu Y J and Cheng W Q. 2014. Research of imager scan mirror’s thermal distortion model for image navigation and registration. Aerospace Shanghai, 31(2): 26–29, 72 (

唐飞, 董慧杰, 李南, 刘彩虹. 2016. FY-3B微波成像仪资料的地理定位误差与订正. 遥感学报, 20(6): 1342–1351

Tang F, Dong H J, Li N and Liu C H. 2016. Geolocation errors and correction of FY-3B microwave radiation imager measurements. Journal of Remote Sensing, 20(6): 1342–1351 (

唐世浩, 邱红, 马刚. 2016. 风云气象卫星主要技术进展. 遥感学报, 20(5): 842–849

Tang S H, Qiu H and Ma G. 2016. Review on progress of the Fengyun meteorological satellite. Journal of Remote Sensing, 20(5): 842–849 (

Tehranian S, Carr J L, Yang S, Madani H, Vasanth S, McKenzie K, Schmit T J, Swaroop A and DiRosario R. 2008. Remapping GOES imager instrument data for South American operations, implementing the XGOHI system//Proceedings of the 5th GOES User’s Conference. New Orleans: [s.n.]

Virgilio V N. 2015. Geolocation of remotely sensed pixels by introspective landmarking. U.S., No. 8, 942, 421 B1

许健民, 杨军, 张志清, 孙安来. 2010. 我国气象卫星的发展与应用. 气象, 36(7): 94–100

Xu J M, Yang J, Zhang Z Q and Sun A L. 2010. Chinese meteorological satellitas, achievements and applications. Meteorological Monthly, 36(7): 94–100 (

Yang J, Zhang Z Q, Wei C Y, Lu F and Guo Q. 2017. Introducing the new generation of Chinese geostationary weather satellites, Fengyun-4. Bulletin of the American Meteorological Society, 98(8): 1637–1658

章仁为. 1998. 卫星轨道姿态动力学与控制. 北京: 北京航空航天大学出版社: 7–17

Zhang R W. 1998. Satellite Orbit Attitude Dynamics and Control. Beijing: Beihang University Press: 7–17

张志清, 董瑶海, 丁雷, 王淦泉, 方翔, 张效信, 黄富祥. 2016. 我国首颗第二代静止气象卫星风云-4升空. 国际太空, (12): 6–12

Zhang Z Q, Dong Y H, Ding L, Wang G Q, Fang X, Zhang X X and Huang F X. 2016. China’s first second-generation FY-4 meteorological satellite launched. Aerospace China, (12): 6–12

张志清, 陆风, 方翔, 唐世浩, 张晓虎, 许映龙, 韩威, 聂肃平, 申彦波, 周毓荃. 2017. FY-4 卫星应用和发展. 上海航天, 34(4): 8–19

Zhang Z Q, Lu F, Fang X, Tang S H, Zhang X H, Xu Y L, Han W, Nie S P, Shen Y B and Zhou Y Q. 2017. Application and development of FY-4 meteorological satellite. Aerospace Shanghai, 34(4): 8–19 (

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